The ability to detect the onset of a gear system failure via accelerometer measurements is of interest in a research environment as well as in gear systems deployed in the field. The goal in either case is to detect a failure as early as possible while simultaneously minimizing the risk of false shutdowns.

The accelerometer based gear health monitoring system described herein was developed for use in a laboratory setting for monitoring power recirculating gear tests. In this environment it is desirable to detect the early onset of failures so the primary failure mode as well as the time to failure can be accurately determined. Minimizing false shutdowns is also critical to maximizing rig uptime and testing efficiency.

The signal processing algorithm uses even-angle resampling along with time synchronous averaging to minimize the influence of vibration sources other than the gear mesh. In the case of hunting tooth ratio gearsets it is shown that it is possible to completely separate the damage response of each gear in the pair from a single accelerometer signal using these techniques. The average log ratio (ALR) algorithm is then employed to monitor the time synchronous averaged signals for the onset of damage. A summary of these signal processing concepts is given, along with an overview of system hardware, signal processing workflow, and sample data.